The Internet of Things (IoT) has completely changed how we architect modern enterprise geospatial systems. We now must consider stream services (maybe traffic or weather), cloud storage options (possibly buckets or blobs) and how we process large datasets over distributed infrastructure.
These are important considerations when analysing your data to make informed decisions and improve business processes.
ArcGIS supports a myriad of data sources from unstructured no sql databases such as Hadoop and MarkLogic, to in memory databases such as SAP HANA, along with your traditional relational database management systems (RDBMS) such as Microsoft SQL Server, Oracle, Teradata and more.
But the Platform has now evolved, supporting native access to cloud stores such as Amazon’s Simple Storage Service (S3) buckets and Microsoft’s Azure Blob container providing access to a directory of hosted datasets. This is useful to support streaming or hot access to data, along with scenarios where you want to provide access to data anywhere.
So, with changes in how we can ingest high volumes of data from many disparate data sources, how do we architect our system to cope with the load?
You guessed it, distributed computing!
ArcGIS Enterprise 10.5 introduced new server roles such as the GeoAnalytics server, designed for implementation on an independent machine. GeoAnalytics server connects to your ArcGIS Enterprise Portal allowing you to distribute compute processing to dedicated machines without placing burden on your Portal, or other ArcGIS roles such as the GeoEvent server for real-time mapping and analytics, or the ArcGIS Image server for serving, processing & extracting image, raster & remotely sensed data.
This architectural change aligns perfectly with cloud service providers such as Amazon Web Services (AWS) and Microsoft’s Azure cloud where you can leverage pre-configured templates (images) and cloud deployment tools to rapidly implement ArcGIS technology with a distributed compute architecture.
This means you can immediately gain benefits from our latest features, functions and apps within 10.5.1, while dramatically reducing the time it takes to process large Imagery and Feature datasets.
These cloud resources also reduce application management overhead, by providing patterns of deployment to build your enterprise GIS upon.
Image: Distributed processing undertaken by GeoAnalytics server on Microsoft Azure cloud infrastructure.
Today, the Platform provides a true system of systems allowing you to combine multiple data sources into a system of record. This single point of truth can be published into apps such as Insights for ArcGIS providing a system of insight to help make sense of your data. Our latest apps for constituent or customer engagement, such as Story Maps acts as a System of engagement to articulate your message in a concise, graphic and interactive medium.
Image: Insights for ArcGIS. System of insight within the data analytic work flow, allowing users to make decisions from the Big Data assets within their organisation.
It has been an exciting year at Esri Australia, with some major technology advancements. I can’t wait to see where 2018 takes us!
Esri Australia Technical Blog 